Edgar Eduardo Yáñez Angarita, V. Núñez-López, A. Ramírez Ramírez, Edgar Fernando Castillo Monroy, A. Faaij
{"title":"哥伦比亚含油气盆地CO2- eor潜力的快速筛选和概率估计以及相关的地质CO2储存","authors":"Edgar Eduardo Yáñez Angarita, V. Núñez-López, A. Ramírez Ramírez, Edgar Fernando Castillo Monroy, A. Faaij","doi":"10.1144/petgeo2020-110","DOIUrl":null,"url":null,"abstract":"Estimating the oil recovery potential using CO2 (CO2-EOR) at a national level is resource-intensive at a scale that is not usually available. The aim of this study is two-fold: first, the potential for CO2 storage and enhanced oil recovery (EOR) in Colombia is evaluated; and, second, the results from two different calculation methods (stochastic and deterministic) are compared when there is lack of information for a quick screening of suitable oilfields. The deterministic approach is based on expert insight and data found in the literature; while, the stochastic uses statistical data from two different databases (commercial and simulation-based results) to run a Monte Carlo simulation. Potential estimates based on typical values from the literature (deterministic) results in 277 MMbbl (million barrels) of oil and 36 Mt (million tonnes) of CO2. In contrast, a probabilistic-based method using a wide simulation database (stochastic) provides higher values of 690 MMbbl of oil and 203 Mt of CO2. Results using simulation-based and commercial project data also show significant differences. The volume of CO2 injected, which affects the recovery factor, is usually 100% hydrocarbon pore volume (HCPV) in simulation, while commercial projects have nowadays regularly increased from 30% to exceed the 100% threshold. A combination of these approaches avoids a resource-intensive estimation process and effectively provides a more realistic picture of the feasibility of applying CO2-EOR technologies. Thematic collection: This article is part of the Geoscience for CO2 storage collection available at: https://www.lyellcollection.org/cc/geoscience-for-co2-storage","PeriodicalId":49704,"journal":{"name":"Petroleum Geoscience","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Rapid screening and probabilistic estimation of the potential for CO2-EOR and associated geological CO2 storage in Colombian petroleum basins\",\"authors\":\"Edgar Eduardo Yáñez Angarita, V. Núñez-López, A. Ramírez Ramírez, Edgar Fernando Castillo Monroy, A. Faaij\",\"doi\":\"10.1144/petgeo2020-110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimating the oil recovery potential using CO2 (CO2-EOR) at a national level is resource-intensive at a scale that is not usually available. The aim of this study is two-fold: first, the potential for CO2 storage and enhanced oil recovery (EOR) in Colombia is evaluated; and, second, the results from two different calculation methods (stochastic and deterministic) are compared when there is lack of information for a quick screening of suitable oilfields. The deterministic approach is based on expert insight and data found in the literature; while, the stochastic uses statistical data from two different databases (commercial and simulation-based results) to run a Monte Carlo simulation. Potential estimates based on typical values from the literature (deterministic) results in 277 MMbbl (million barrels) of oil and 36 Mt (million tonnes) of CO2. In contrast, a probabilistic-based method using a wide simulation database (stochastic) provides higher values of 690 MMbbl of oil and 203 Mt of CO2. Results using simulation-based and commercial project data also show significant differences. The volume of CO2 injected, which affects the recovery factor, is usually 100% hydrocarbon pore volume (HCPV) in simulation, while commercial projects have nowadays regularly increased from 30% to exceed the 100% threshold. A combination of these approaches avoids a resource-intensive estimation process and effectively provides a more realistic picture of the feasibility of applying CO2-EOR technologies. Thematic collection: This article is part of the Geoscience for CO2 storage collection available at: https://www.lyellcollection.org/cc/geoscience-for-co2-storage\",\"PeriodicalId\":49704,\"journal\":{\"name\":\"Petroleum Geoscience\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Petroleum Geoscience\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1144/petgeo2020-110\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum Geoscience","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1144/petgeo2020-110","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Rapid screening and probabilistic estimation of the potential for CO2-EOR and associated geological CO2 storage in Colombian petroleum basins
Estimating the oil recovery potential using CO2 (CO2-EOR) at a national level is resource-intensive at a scale that is not usually available. The aim of this study is two-fold: first, the potential for CO2 storage and enhanced oil recovery (EOR) in Colombia is evaluated; and, second, the results from two different calculation methods (stochastic and deterministic) are compared when there is lack of information for a quick screening of suitable oilfields. The deterministic approach is based on expert insight and data found in the literature; while, the stochastic uses statistical data from two different databases (commercial and simulation-based results) to run a Monte Carlo simulation. Potential estimates based on typical values from the literature (deterministic) results in 277 MMbbl (million barrels) of oil and 36 Mt (million tonnes) of CO2. In contrast, a probabilistic-based method using a wide simulation database (stochastic) provides higher values of 690 MMbbl of oil and 203 Mt of CO2. Results using simulation-based and commercial project data also show significant differences. The volume of CO2 injected, which affects the recovery factor, is usually 100% hydrocarbon pore volume (HCPV) in simulation, while commercial projects have nowadays regularly increased from 30% to exceed the 100% threshold. A combination of these approaches avoids a resource-intensive estimation process and effectively provides a more realistic picture of the feasibility of applying CO2-EOR technologies. Thematic collection: This article is part of the Geoscience for CO2 storage collection available at: https://www.lyellcollection.org/cc/geoscience-for-co2-storage
期刊介绍:
Petroleum Geoscience is the international journal of geoenergy and applied earth science, and is co-owned by the Geological Society of London and the European Association of Geoscientists and Engineers (EAGE).
Petroleum Geoscience transcends disciplinary boundaries and publishes a balanced mix of articles covering exploration, exploitation, appraisal, development and enhancement of sub-surface hydrocarbon resources and carbon repositories. The integration of disciplines in an applied context, whether for fluid production, carbon storage or related geoenergy applications, is a particular strength of the journal. Articles on enhancing exploration efficiency, lowering technological and environmental risk, and improving hydrocarbon recovery communicate the latest developments in sub-surface geoscience to a wide readership.
Petroleum Geoscience provides a multidisciplinary forum for those engaged in the science and technology of the rock-related sub-surface disciplines. The journal reaches some 8000 individual subscribers, and a further 1100 institutional subscriptions provide global access to readers including geologists, geophysicists, petroleum and reservoir engineers, petrophysicists and geochemists in both academia and industry. The journal aims to share knowledge of reservoir geoscience and to reflect the international nature of its development.